Abstract Background Odontometric analysis plays an important role in forensic identification due to the durability of dental tissues. In heterogeneous populations such as India, applying generalized standards may introduce systematic bias, highlighting the need for region-specific models. This study evaluated the forensic applicability of three-dimensional intraoral scan-derived odontometric parameters for sex classification and stature estimation in adults from North Maharashtra. Methods A cross-sectional study was conducted among 320 healthy adults (160 males, 160 females; mean age 23.2 ± 3.03 years) selected through stratified random sampling. Inclusion criteria required fully erupted, caries-free, unrestored permanent canines and first molars. Stature was measured using a standardized stadiometer. Digital impressions were obtained with an intraoral scanner, and three-dimensional software was used to measure maxillary and mandibular intercanine width, canine mesiodistal and buccolingual widths, and cumulative mesiodistal width of six anterior teeth. Independent t-tests or Mann–Whitney U tests assessed sex differences. Spearman’s correlation and multiple linear regression were used for stature prediction, and binary logistic regression with receiver operating characteristic (ROC) analysis evaluated sex classification performance ( p < 0.05). Results Significant sexual dimorphism was observed in maxillary parameters, with males exhibiting larger intercanine width ( p = 0.003), canine mesiodistal width ( p = 0.001), canine buccolingual width ( p = 0.049), and cumulative anterior mesiodistal width ( p = 0.010), while mandibular parameters showed no significant differences. Stature demonstrated positive correlations with maxillary intercanine width ( r = 0.26, p = 0.001), maxillary canine mesiodistal width ( r = 0.22, p = 0.005), and cumulative anterior width ( r = 0.13, p = 0.012). Linear regression indicated a 0.79 cm increase in stature per 1 mm increase in maxillary intercanine width ( p = 0.002), with the final model explaining 44% of stature variance in the testing dataset. Logistic regression demonstrated moderate discriminatory performance for sex classification (AUC = 0.841 training; 0.782 testing). Conclusions Maxillary odontometric parameters demonstrated significant sexual dimorphism and modest but meaningful associations with stature in this North Maharashtra population. The derived population-specific models showed moderate predictive performance and may serve as supportive tools for forensic identification when dental remains are available. Three-dimensional digital measurement enhances reproducibility and methodological reliability in forensic odontology.
Agrawal et al. (Mon,) studied this question.